2026 OpenClaw Multi-Agent Scheduling: sessions_spawn runtime=acp vs subagent Decision Matrix, streamTo Misconfiguration Triage, and ACP 1008 Handshake Failure Runbook

Six common misreads in multi-agent scheduling (recognize them before changing runtime)

1. Default runtime=acp without an ACP bridge: main channel chat works, but every spawn returns ACP_TURN_FAILED—the root cause is an unregistered acpx or offline queue owner, not model quota.
2. Passing streamTo / resumeSessionId under runtime=subagent: these fields serve ACP session continuation only; subagent uses in-Gateway embedded RPC, and misconfiguration yields invalid parameters or silently dropped fields that look like “the child Agent got no context.”
3. Treating every 1008 as a Docker pairing issue: in Compose scenarios see the trustedProxies article; on bare-metal acp paths, 1008 more often reflects handshake version skew or bridge startup races.
4. Testing spawn before reload after upgrade: CLI is new but Gateway is an old process—acp and subagent stacks can split. Align the acceptance ladder first, then test scheduling.
5. Ignoring the acpx startup probe on Windows: provider extensions slow startup; ACP handshake fires before the bridge is ready and logs show invalid handshake. Use OPENCLAW_ACPX_RUNTIME_STARTUP_PROBE to extend or retry.
6. Mixing Completions and Responses API without checking streamTo auto-fill: 2026 routing infers streamTo targets for Responses sessions; Completions paths do not—spawn looks broken when the real issue is API shape plus runtime mismatch.

In 2026 upstream explicitly splits sessions_spawn into two mutually exclusive runtimes. runtime=acp talks to an external acpx process through the ACP bridge and supports streamTo to stream child Agent output back to the main session UI. runtime=subagent starts a lightweight sub-agent inside the Gateway process—lower latency, no acpx dependency, but no ACP continuation fields.

Choosing the wrong runtime and stacking invalid fields is the most time-consuming “false complexity” on call. Align the path first, then tune models and tool allowlists (see the tools.profile triage guide).

Treat every spawn call as a scheduling contract you archive in the ticket: runtime, whether UI streaming is required, whether the main session uses Completions or Responses, and the fallback path (subagent or rollback). Without that contract, “same Gateway worked yesterday, fails today” is hard to explain—changes usually land in template fields or API shape, not the Gateway binary itself.

Production teams that skip this contract often burn hours re-tuning prompts while the JSON still carries streamTo: "main" on a subagent path copied from an old acp example. The fix is structural, not lexical.

Another pattern we see in 2026 tickets: the main Agent template was authored for Cursor IDE acp flows, then deployed unchanged to a headless Gateway that only supports subagent batch work. The spawn call succeeds intermittently when acpx happens to be running locally, then fails in CI—creating the illusion of flaky infrastructure rather than a runtime mismatch.

Before opening a severity-1 bridge outage, confirm whether any spawn in the last hour actually required acp semantics. If every failing task is read-only background research with no UI consumer, switching to subagent is often the correct permanent fix, not a temporary workaround.

runtime=acp vs runtime=subagent: which stack to use

Rule of thumb: need UI streaming, resume an existing ACP session, or align with Cursor/IDE acpx → acp. Need in-Gateway closure, low dependency, or acp is currently down → subagent. The table below covers four task shapes common in production tickets (not exhaustive, but roughly 80% of cases).

When in doubt, run a one-line subagent probe first. If it passes, the Gateway scheduling stack is healthy and the failure is almost certainly acp-specific or field misconfiguration—not model quality or task wording.

streamTo / resumeSessionId: acp-only fields and misconfiguration triage

Many “spawn parameters look correct but child Agent returns empty” reports come from field and runtime cross-contamination. On the subagent path the Gateway strips or rejects ACP-only fields. If the main Agent template copied streamTo: "main" from a Completions example but the call uses runtime=subagent, logs often show only a generic RPC error—not “invalid field”—so you must inspect the call JSON.

Under runtime=acp, resumeSessionId continues an existing acpx session (for example multiple spawns in one thread). streamTo directs child Agent token streams to the main Control UI or a specified channel render target.

2026 Responses API routing may auto-infer streamTo when the main session is bound to Responses shape and the field is omitted. Completions shape does not auto-fill. Migrating from Responses to Completions without updating spawn templates produces “streaming worked before, child now runs silently in background”—a regression unrelated to upgrade, purely API shape plus runtime combination.

Run a field-stripping experiment during triage: copy the failing call JSON, remove streamTo and resumeSessionId, set runtime=subagent, retry. If subagent succeeds immediately, the original fault is almost certainly acp path or misconfiguration—not task content or model capability. If it still fails, move to pairing, token, or tool surface triage. Put this experiment at runbook step 4 so on-call does not spin in acp logs.

Document the before/after JSON in the ticket. Future you (or the next shift) should not re-run the same blind acp retries.

When auditing templates, search for streamTo outside acp blocks. Many repos carry a shared spawn snippet copied from Responses-era examples. Lint rules that flag runtime=subagent plus any of streamTo, resumeSessionId, or acpSession catch most regressions before deploy.

If UI streaming is required and stripping fields breaks the product experience, do not force subagent as a permanent state—record the business constraint in the ticket and prioritize bridge repair or topology change instead of silently accepting silent background execution.

// acp: UI streaming + optional resume
{
  "tool": "sessions_spawn",
  "runtime": "acp",
  "task": "Research competitor pricing and output a table",
  "streamTo": "main",
  "resumeSessionId": "acp-sess-abc123"
}

// subagent: in-Gateway closure—no streamTo
{
  "tool": "sessions_spawn",
  "runtime": "subagent",
  "task": "Batch-rename files under logs directory"
}

// common misconfiguration: subagent with ACP fields
{
  "runtime": "subagent",
  "streamTo": "main"
}

ACP handshake failure triage: ACP_TURN_FAILED, 1008, queue owner

When runtime=acp fails but main chat still works, route by log fingerprint—do not mix with “Gateway completely silent” (that class goes to channel/model articles).

Capture one full spawn attempt with timestamps aligned to Gateway and acpx logs. Handshake failures often span sub-second windows; without aligned clocks you chase the wrong layer.

Start with the smallest reproducible acp spawn—not the full production task with tools and long context. A one-sentence read-only probe isolates handshake from tool allowlist and model latency. If the minimal acp probe fails but minimal subagent passes, you have narrowed the fault to bridge/acpx, not Gateway scheduling generally.

WebSocket 1008 on acp alone frequently correlates with version skew between CLI, Gateway daemon, and acpx binary. Record all three version strings in the ticket before attempting rollback; pinning only Gateway while acpx stays on an older channel recreates 1008 within minutes.

Windows and OPENCLAW_ACPX_RUNTIME_STARTUP_PROBE

On Windows, provider extensions and Defender scans often push acpx cold start past several seconds. If spawn fires before the bridge is ready, you see ACP_TURN_FAILED or invalid handshake—not necessarily a version bug.

Set OPENCLAW_ACPX_RUNTIME_STARTUP_PROBE=1 (exact semantics per your OpenClaw version docs) so Gateway waits one extra acpx health probe round before the first spawn, reducing race false failures.

If it still fails, run a minimal subagent task on the same machine to prove the Gateway scheduling stack is intact, then isolate acpx install/permission issues—do not misread slow Windows startup as “must roll back OpenClaw version.”

Division of labor with the upgrade guardrails article: that page covers full-site probe/ACP regression after version migration; this page covers stable versions where only spawn scheduling or occasional handshake failure appears. Chain them: confirm upgrade ladder passed, then enter this runtime matrix—otherwise split-brain looks like streamTo misconfiguration.

On Windows, also check whether acpx is blocked by Controlled Folder Access or corporate endpoint policy—the process starts but bridge registration never completes, producing queue owner unavailable rather than an obvious permission error. Startup probe gives acpx time to finish registration after policy-delayed I/O.

Document probe settings in your environment variable management system, not only in a one-off PowerShell session. Ephemeral shell exports explain “it worked in my terminal yesterday” incidents when a service restart drops the variable.

# Windows: extend acpx startup probe (example)
$env:OPENCLAW_ACPX_RUNTIME_STARTUP_PROBE = "1"
openclaw gateway status
openclaw gateway probe

# Minimal subagent probe (no streamTo)
# Trigger equivalent sessions_spawn via Control UI or CLI, runtime=subagent

When acp breaks: keep fixing vs pin vs fallback decision matrix

Not every red acp spawn warrants rollback. Use impact surface to choose among bridge repair, temporary subagent, and digest pin/rollback.

Seven-step runbook: select, probe, spawn, triage, fallback, document

1. Freeze call JSON: record runtime, presence of streamTo / resumeSessionId, main session API shape (Completions vs Responses).
2. Gateway baseline: openclaw gateway status + gateway probe; after upgrade perform exactly one reload (see upgrade guardrails).
3. Selection self-check: need UI streaming → acp + streamTo; background task → subagent, strip ACP fields.
4. Minimal spawn probe: subagent one-line read-only task first; pass means scheduling stack OK, fail means pairing/token.
5. acp-specific: confirm acpx process and bridge; on Windows enable OPENCLAW_ACPX_RUNTIME_STARTUP_PROBE; capture 1008 / queue owner logs.
6. Fallback or rollback: acp fails two rounds → ticket marks subagent fallback; both paths dead → digest rollback.
7. Close-out metrics: write spawn success rate, fallback ratio, MTTR; update internal runtime selection memo.

Steps 3 and 4 should take under five minutes when logs are accessible. If on-call spends longer than fifteen minutes on step 5 without new signal, escalate to bridge/platform owners rather than looping acp retries—each blind retry adds noise to MTTR calculations and may trigger rate limits on upstream model routes unrelated to the handshake fault.

Step 6 deserves explicit ticket language: “temporary runtime=subagent, UI streaming tasks blocked until acp restored” prevents product teams from assuming subagent output will appear in the main chat window. Ambiguous fallback notes cause duplicate tickets from users who never saw child Agent results.

Three metrics to put on every change ticket

• Spawn success rate (by runtime bucket): successful sessions_spawn / total calls in window; when acp bucket falls below 95% but subagent bucket is healthy, fix bridge before swapping models.
• acp→subagent fallback ratio: tasks needing UI streaming should not live on fallback long term; if >30% of tickets use subagent to replace acp for a week, push version pin or topology migration.
• streamTo misconfiguration event count: audit count of streamTo/resumeSessionId on runtime=subagent calls; production target 0 (app-layer lint or template review).

On laptop Gateways mixing acpx, lid-close sleep, and multiple provider plugins, spawn failures get misfiled as “OpenClaw unstable.” Safer pattern: co-locate authoritative Gateway and acpx on an always-on remote Mac; local machine only SSH-forwards Control UI—spawn and probe validate on one node with aligned log timelines.

Review spawn success rate weekly split by runtime bucket, not as a single aggregate. A healthy aggregate can hide acp hovering at 70% while subagent sits at 99%—exactly the pattern that precedes a bridge regression going unnoticed until UI streaming tasks fail in a demo.

The streamTo misconfiguration counter is cheap to implement: log structured warnings when subagent calls include ACP-only keys. Target zero in production; non-zero counts imply template drift or an Agent prompt inventing fields the Gateway will strip.

Closing: runtime selection is a scheduling contract, not prompt tuning

Iterating prompts in the main Agent without checking whether runtime and streamTo match turns ACP handshake issues into the illusion that “multi-agent is down.” Writing the acp/subagent matrix, misconfiguration triage, and subagent fallback into runbooks compresses on-call from blind evening retries to probed, fallback-backed, measured minute-scale incidents.

If you insist on hard-running the acp bridge on a Windows laptop or split-container Docker topology, accept three hidden costs: startup races producing false 1008, Completions/Responses streamTo auto-fill inconsistency, and expanded blast radius when subagent and acp failure surfaces overlap.

For production Gateways needing 24/7 uptime, ticketable spawn, and switchable acp/subagent paths, hosting on MACCOME Mac mini (M4 / M4 Pro) with flexible multi-region leases usually beats fighting queue owner on a closed laptop. Compare public tiers in the multi-region node and lease guide, then chain topology with the SSH dedicated Gateway runbook.

Keep this runbook beside the upgrade guardrails and Docker 1008 articles in your internal wiki. Spawn incidents that begin with runtime misconfiguration should never end in digest rollback; conversely, incidents where both paths fail after a channel upgrade should not waste hours on streamTo template edits. The decision matrices above exist to force that separation early.

When onboarding new operators, walk through one successful acp spawn with streamTo and one subagent spawn without ACP fields on the same Gateway. That ten-minute exercise prevents most of the misreads listed in section one from recurring in your on-call queue.